LIVIVO - Search results -

Search results

Result 1 - 9 of total 9

Search options

Article ; Online: A mechanistic study of Anwei decoction intervention in a rat model of gastric intestinal metaplasia through the endoplasmic reticulum stress - Autophagy pathway.

Wu, De-Kun / Huang, Rui-Cheng / Tang, You-Ming / Jiang, Xian

2024 Volume 87, Page(s) 102317

Abstract: Objective: To investigate the mechanism of Anwei decoction (AWD) intervention on gastric intestinal metaplasia (GIM) using a rat model through the endoplasmic reticulum stress-autophagy pathway.: Methods: Gastric intestinal metaplasia was induced in ... ...

Abstract	Objective: To investigate the mechanism of Anwei decoction (AWD) intervention on gastric intestinal metaplasia (GIM) using a rat model through the endoplasmic reticulum stress-autophagy pathway. Methods: Gastric intestinal metaplasia was induced in rats using 1-methyl-3-nitro-1-nitrosoguanidine. The experiment included a normal control group, a model group, and low-, medium- and high-dose AWD groups. The specificity of intestinal epithelial cells was determined for model establishment and drug efficacy by detecting the protein expression of markers such as MUC2, VILLIN and CDX2 through western blotting (WB). The effects of AWD on endoplasmic reticulum stress and autophagy were evaluated by measuring the mRNA and protein expression levels of endoplasmic reticulum stress markers (PEPK, ATF6, CHOP and caspase-12) and autophagy markers (LC3Ⅱ and Beclin-1) using reverse transcription polymerase chain reaction and the WB method. Furthermore, the ultrastructure of gastric mucosal cells and autophagosome status were observed using transmission electron microscopy. Results: Compared with the model group, the AWD-treated rats exhibited significant improvement in body weight (P < 0.01), reduced protein expression of the intestine epithelial cell-specific markers MUC2, VILLIN, CDX2 and KLF4 (P < 0.01 for all) and increased SOX2 protein expression (P < 0.01). In addition, AWD suppressed the mRNA and protein expression of endoplasmic reticulum stress markers PEPK and ATF6 (P < 0.01 for all) and promoted the mRNA and protein expression of autophagy and apoptosis markers CHOP, caspase-12, LC3Ⅱ and Beclin-1 (P < 0.01 for all). Conclusion: Anwei decoction effectively inhibits the further progression of GIM and prevents the occurrence of gastric mucosal carcinogenesis.
MeSH term(s)	Rats ; Animals ; Signal Transduction ; Beclin-1/genetics ; Beclin-1/pharmacology ; Caspase 12 ; Apoptosis ; RNA, Messenger ; Autophagy ; Endoplasmic Reticulum Stress ; Metaplasia
Chemical Substances	Beclin-1 ; Caspase 12 (EC 3.4.22.-) ; RNA, Messenger
Language	English
Publishing date	2024-02-01
Publishing country	Scotland
Document type	Journal Article
ZDB-ID	204424-9
ISSN	1532-3072 ; 0040-8166
ISSN (online)	1532-3072
ISSN	0040-8166
DOI	10.1016/j.tice.2024.102317
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1016: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Book ; Online: Deciphering Digital Detectives

Wu, Dekun / Shi, Haochen / Sun, Zhiyuan / Liu, Bang

Understanding LLM Behaviors and Capabilities in Multi-Agent Mystery Games

2023

Abstract: In this study, we explore the application of Large Language Models (LLMs) in "Jubensha" (Chinese murder mystery role-playing games), a novel area in AI-driven gaming. We introduce the first Chinese dataset specifically for Jubensha, including character ... ...

Abstract	In this study, we explore the application of Large Language Models (LLMs) in "Jubensha" (Chinese murder mystery role-playing games), a novel area in AI-driven gaming. We introduce the first Chinese dataset specifically for Jubensha, including character scripts and game rules, to foster AI agent development in this complex narrative environment. Our work also presents a unique multi-agent interaction framework using LLMs, allowing AI agents to autonomously engage in the game, enhancing the dynamics of Jubensha gameplay. To evaluate these AI agents, we developed specialized methods targeting their mastery of case information and reasoning skills. Furthermore, we incorporated the latest advancements in in-context learning to improve the agents' performance in critical aspects like information gathering, murderer detection, and logical reasoning. The experimental results validate the effectiveness of our proposed methods. This work aims to offer a fresh perspective on understanding LLM capabilities and establish a new benchmark for evaluating large language model-based agents to researchers in the field.
Keywords	Computer Science - Artificial Intelligence ; I.2.0 ; I.2.1 ; I.2.7
Subject code	006
Publishing date	2023-12-01
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Juan-tong-yin potentially impacts endometriosis pathophysiology by enhancing autophagy of endometrial stromal cells via unfolded protein reaction-triggered endoplasmic reticulum stress.

Meng, Fengyun / Li, Jing / Dong, Kun / Bai, Rui / Liu, Qiyu / Lu, Shijin / Liu, Ying / Wu, Dekun / Jiang, Chen / Li, Weihong

Journal of ethnopharmacology

2024 Volume 325, Page(s) 117859

Abstract: Ethnopharmacological relevance: Endometriosis (EMs) is characterized by inflammatory lesions, dysmenorrhea, infertility, and chronic pelvic pain. Single-target medications often fail to provide systemic therapeutic results owing to the complex mechanism ...

Abstract	Ethnopharmacological relevance: Endometriosis (EMs) is characterized by inflammatory lesions, dysmenorrhea, infertility, and chronic pelvic pain. Single-target medications often fail to provide systemic therapeutic results owing to the complex mechanism underlying endometriosis. Although traditional Chinese medicines-such as Juan-Tong-Yin (JTY)-have shown promising results, their mechanisms of action remain largely unknown. Aim of the study: To elucidate the therapeutic mechanism of JTY in EMs, focusing on endoplasmic reticulum (ER) stress-induced autophagy. Materials and methods: The major components of JTY were detected using high-performance liquid chromatography-mass spectrometry (HPLC-MS). The potential mechanism of JTY in EMs treatment was predicted using network pharmacological analysis. Finally, the pathogenesis of EMs was validated in a clinical case-control study and the molecular mechanism of JTY was validated in vitro using endometrial stromal cells (ESCs). Results: In total, 241 compounds were analyzed and identified from JTY using UPLC-MS. Network pharmacology revealed 288 targets between the JTY components and EMs. Results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses indicated that regulating autophagy, migration, apoptosis, and inflammation were the key mechanisms of JTY in treating EMs. Meanwhile, we found that protein kinase R-like endoplasmic reticulum kinase (PERK), Beclin-1, and microtubule-associated protein light chain 3 B (LC3B) expressions were lower in endometria of patients with EMs than in those with normal eutopic endometria (p < 0.05). Additionally, during in vitro experiments, treatment with 20% JTY-containing serum significantly suppressed ESC proliferation, achieving optimal effects after 48 h. Electron microscopy revealed significantly increased autophagy flux in the JTY group compared with the control group. Moreover, JTY treatment significantly reduced the migratory and invasive abilities of ESCs and upregulated protein expression of PERK, eukaryotic initiation factor 2α (eIF2α)/phospho-eukaryotic initiation factor 2α (p-eIF2α), activating Transcription Factor-4 (ATF4), Beclin-1, and LC3BII/I, while subsequently downregulating NOD-like receptor thermal protein domain associated protein 3 (NLRP3) and interleukin 18 (IL-18) expression. However, administration of GSK2656157-a highly selective PERK inhibitor-reversed these changes. Conclusion: JTY ameliorates EMs by activating PERK associated with unfolded protein reaction, enhancing cell ER stress and autophagy, improving the inflammatory microenvironment, and decreasing the migration and invasion of ESCs.
MeSH term(s)	Female ; Humans ; Signal Transduction ; Beclin-1/metabolism ; Endometriosis/pathology ; Case-Control Studies ; Chromatography, Liquid ; Tandem Mass Spectrometry ; Endoplasmic Reticulum Stress ; Autophagy ; Apoptosis ; Stromal Cells/metabolism ; Stromal Cells/pathology ; Peptide Initiation Factors/metabolism ; Peptide Initiation Factors/pharmacology
Chemical Substances	Beclin-1 ; Peptide Initiation Factors
Language	English
Publishing date	2024-02-03
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	134511-4
ISSN	1872-7573 ; 0378-8741
ISSN (online)	1872-7573
ISSN	0378-8741
DOI	10.1016/j.jep.2024.117859
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1494: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Book ; Online: Sports Video Analysis on Large-Scale Data

Wu, Dekun / Zhao, He / Bao, Xingce / Wildes, Richard P.

2022

Abstract: This paper investigates the modeling of automated machine description on sports video, which has seen much progress recently. Nevertheless, state-of-the-art approaches fall quite short of capturing how human experts analyze sports scenes. There are ... ...

Abstract	This paper investigates the modeling of automated machine description on sports video, which has seen much progress recently. Nevertheless, state-of-the-art approaches fall quite short of capturing how human experts analyze sports scenes. There are several major reasons: (1) The used dataset is collected from non-official providers, which naturally creates a gap between models trained on those datasets and real-world applications; (2) previously proposed methods require extensive annotation efforts (i.e., player and ball segmentation at pixel level) on localizing useful visual features to yield acceptable results; (3) very few public datasets are available. In this paper, we propose a novel large-scale NBA dataset for Sports Video Analysis (NSVA) with a focus on captioning, to address the above challenges. We also design a unified approach to process raw videos into a stack of meaningful features with minimum labelling efforts, showing that cross modeling on such features using a transformer architecture leads to strong performance. In addition, we demonstrate the broad application of NSVA by addressing two additional tasks, namely fine-grained sports action recognition and salient player identification. Code and dataset are available at https://github.com/jackwu502/NSVA.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2022-08-09
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Bimetallic Covalent Organic Frameworks for Constructing Multifunctional Electrocatalyst.

Wu, Dekun / Xu, Qing / Qian, Jing / Li, Xiaopeng / Sun, Yuhan

Chemistry (Weinheim an der Bergstrasse, Germany)

2019 Volume 25, Issue 12, Page(s) 3105–3111

Abstract: Covalent organic frameworks (COFs) are a new class of crystalline porous polymers comprised mainly of carbon atoms, and are versatile for the integration of heteroatoms such as B, O, and N into the skeletons. The designable structure and abundant ... ...

Abstract	Covalent organic frameworks (COFs) are a new class of crystalline porous polymers comprised mainly of carbon atoms, and are versatile for the integration of heteroatoms such as B, O, and N into the skeletons. The designable structure and abundant composition render COFs useful as precursors for heteroatom-doped porous carbons for energy storage and conversion. Herein, we describe a multifunctional electrochemical catalyst obtained through pyrolysis of a bimetallic COF. The catalyst possesses hierarchical pores and abundant iron and cobalt nanoparticles embedded with standing carbon layers. By integrating these features, the catalyst exhibits excellent electrochemical catalytic activity in the oxygen reduction reaction (ORR), with a 50 mV positive half-wave potential, a higher limited diffusion current density, and a much smaller Tafel slope than a Pt-C catalyst. Moreover, the catalyst displays superior electrochemical performance toward the hydrogen evolution reaction (HER), with overpotentials of -0.26 V and -0.33 V in acidic and alkaline aqueous solution, respectively, at a current density of 10 mA cm
Language	English
Publishing date	2019-02-04
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1478547-x
ISSN	1521-3765 ; 0947-6539
ISSN (online)	1521-3765
ISSN	0947-6539
DOI	10.1002/chem.201805550
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Details ▾
- Full text online
- Order with fees

Book ; Online: A General FOFE-net Framework for Simple and Effective Question Answering over Knowledge Bases

Wu, Dekun / Nosirova, Nana / Jiang, Hui / Xu, Mingbin

2019

Abstract: Question answering over knowledge base (KB-QA) has recently become a popular research topic in NLP. One popular way to solve the KB-QA problem is to make use of a pipeline of several NLP modules, including entity discovery and linking (EDL) and relation ... ...

Abstract	Question answering over knowledge base (KB-QA) has recently become a popular research topic in NLP. One popular way to solve the KB-QA problem is to make use of a pipeline of several NLP modules, including entity discovery and linking (EDL) and relation detection. Recent success on KB-QA task usually involves complex network structures with sophisticated heuristics. Inspired by a previous work that builds a strong KB-QA baseline, we propose a simple but general neural model composed of fixed-size ordinally forgetting encoding (FOFE) and deep neural networks, called FOFE-net to solve KB-QA problem at different stages. For evaluation, we use two popular KB-QA datasets, SimpleQuestions and WebQSP, and a newly created dataset, FreebaseQA. The experimental results show that FOFE-net performs well on KB-QA subtasks, entity discovery and linking (EDL) and relation detection, and in turn pushing overall KB-QA system to achieve strong results on all datasets. Comment: 11 pages
Keywords	Computer Science - Computation and Language ; Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2019-03-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: ENT-DESC

Cheng, Liying / Wu, Dekun / Bing, Lidong / Zhang, Yan / Jie, Zhanming / Lu, Wei / Si, Luo

Entity Description Generation by Exploring Knowledge Graph

2020

Abstract: Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language description. Existing datasets, such as WIKIBIO, WebNLG, and E2E, basically have a ... ...

Abstract	Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language description. Existing datasets, such as WIKIBIO, WebNLG, and E2E, basically have a good alignment between an input triple/pair set and its output text. However, in practice, the input knowledge could be more than enough, since the output description may only cover the most significant knowledge. In this paper, we introduce a large-scale and challenging dataset to facilitate the study of such a practical scenario in KG-to-text. Our dataset involves retrieving abundant knowledge of various types of main entities from a large knowledge graph (KG), which makes the current graph-to-sequence models severely suffer from the problems of information loss and parameter explosion while generating the descriptions. We address these challenges by proposing a multi-graph structure that is able to represent the original graph information more comprehensively. Furthermore, we also incorporate aggregation methods that learn to extract the rich graph information. Extensive experiments demonstrate the effectiveness of our model architecture. Comment: 11 pages, 6 figures, accepted by EMNLP 2020
Keywords	Computer Science - Computation and Language
Subject code	004
Publishing date	2020-04-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings

Chen, Bao Xin / Sahdev, Raghavender / Wu, Dekun / Zhao, Xing / Papagelis, Manos / Tsotsos, John K.

2019

Abstract: Scene Classification has been addressed with numerous techniques in computer vision literature. However, with the increasing number of scene classes in datasets in the field, it has become difficult to achieve high accuracy in the context of robotics. In ...

Abstract	Scene Classification has been addressed with numerous techniques in computer vision literature. However, with the increasing number of scene classes in datasets in the field, it has become difficult to achieve high accuracy in the context of robotics. In this paper, we implement an approach which combines traditional deep learning techniques with natural language processing methods to generate a word embedding based Scene Classification algorithm. We use the key idea that context (objects in the scene) of an image should be representative of the scene label meaning a group of objects could assist to predict the scene class. Objects present in the scene are represented by vectors and the images are re-classified based on the objects present in the scene to refine the initial classification by a Convolutional Neural Network (CNN). In our approach we address indoor Scene Classification task using a model trained with a reduced pre-processed version of the Places365 dataset and an empirical analysis is done on a real-world dataset that we built by capturing image sequences using a GoPro camera. We also report results obtained on a subset of the Places365 dataset using our approach and additionally show a deployment of our approach on a robot operating in a real-world environment.
Keywords	Computer Science - Robotics ; Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2019-08-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Standing Carbon-Supported Trace Levels of Metal Derived from Covalent Organic Framework for Electrocatalysis.

Xu, Qing / Zhang, Hao / Guo, Yu / Qian, Jing / Yang, Shuai / Luo, Dan / Gao, Peng / Wu, Dekun / Li, Xiaopeng / Jiang, Zheng / Sun, Yuhan

Small (Weinheim an der Bergstrasse, Germany)

2019 Volume 15, Issue 50, Page(s) e1905363

Abstract: Single atom catalysts (SACs) are receiving increasing interests due to their high theoretical catalytic efficiency and intriguing physiochemical properties. However, most of the synthetic methodologies involve high-temperature treatment. This usually ... ...

Abstract	Single atom catalysts (SACs) are receiving increasing interests due to their high theoretical catalytic efficiency and intriguing physiochemical properties. However, most of the synthetic methodologies involve high-temperature treatment. This usually leads to limited control over the spatial distribution of metal sites and collapse of porous network that result in limited active site exposure. A strategy to construct SAC by using a covalent organic framework as the precursor is reported in this study. The as-prepared catalyst is mainly composed of standing carbon layers with the presence of edge-site hosted metal single atoms. Such structure configuration not only allows full site exposure but also endows the metal site with high intrinsic activity. With a trace amount of cobalt loading (0.17 wt%), the nanorice-shaped catalyst displays promising electrochemical activities toward catalyzing the oxygen reduction reaction in both alkaline and acidic medium. An ultrahigh mass activity of 838 A g
Language	English
Publishing date	2019-11-13
Publishing country	Germany
Document type	Journal Article
ISSN	1613-6829
ISSN (online)	1613-6829
DOI	10.1002/smll.201905363
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- Full text online
- Order with fees

To top

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Order via subito

Inter-library loan at ZB MED